SAT solvers typically have multiple applications. For example, SAT solvers are often used in electronic design automation (EDA) applications, such as automatic test pattern generation (ATPG), formal verification, logic optimization, physical design, and other EDA applications. SAT solvers typically use backtracking algorithms that are based on a Davis-Putman-Logeman-Loveland (DPLL) procedure with nonchronological backtracking and conflict-based learning. In addition, SAT solvers typically use techniques such as Boolean Constraint Propagation (BCP), dynamic restarting, dynamic variable ordering, and efficient management of clause databases.